Quantitative Data Engineer: AI-Driven Data Pipelines

G-Research; Greater London; On-site; GBP 90,000 - 150,000; Full time

Benefits offered by this job

Competitive compensation

Lunch provided

35 days annual leave

9% company pension contributions

Healthcare and life assurance

Monthly company events

Job summary

G-Research in London HQ is seeking a Quantitative Data Engineer who will take data from raw sources through to live signals, working with Quant researchers to engineer features and build scalable pipelines. You will join a team that values collaboration and methodological execution to accelerate discovery.

You will use Python on large-scale compute, apply probability and statistics to real data, and explore LLM-based agents to automate the end-to-end data ingestion to signals, contributing to a

Qualifications

• Minimum 2:1 degree in a quantitative subject such as mathematics, statistics, computer science, physics or engineering.
• Strong software engineering and data skills.
• Experience building production data pipelines with Python data processing.
• Solid knowledge of algorithms, data structures and software fundamentals.
• Comfort applying probability and statistics to real-world data problems.

Responsibilities

• Onboarding new third-party datasets, building pipelines, normalization and validation that make them research-ready.
• Partnering with Quantitative Researchers to engineer features and build signals from onboarded data.
• Using LLM-based agents and workflows to safely automate the pipeline from ingestion to signals.
• Building tools and reusable workflows that help researchers and data scientists scale their work.

Skills

Python

Data pipelines

Algorithms

Statistics

Software engineering

LLM workflows

Collaboration

Education

2:1 degree in quantitative field

Tools

Python

Job description

G-Research in London HQ is seeking a Quantitative Data Engineer who will take data from raw sources through to live signals, working with Quant researchers to engineer features and build scalable pipelines. You will join a team that values collaboration and methodological execution to accelerate discovery.

You will use Python on large-scale compute, apply probability and statistics to real data, and explore LLM-based agents to automate the end-to-end data ingestion to signals, contributing to a